Attempts have been made to take radar signals received from the aircraft radar system, convert it to a reflectivity value, and store it in a location in a three-dimensional (3-D) weather buffer relative to the range associated with the radar signal. The 3-D weather buffer is an array of computer memory that includes data that describes a distribution of a weather reflectivity within a three-dimensional space. In other attempts, radar return signal power is converted to reflectivity based on certain assumptions, and used to populate elements of a 3D weather buffer.
A problem with earlier attempts is that ground clutter contamination of the desired weather signal occurs. Previous attempts to prevent ground clutter contamination have used calculations of antenna beam proximity to the assumed location of the ground, and assumptions of the ground signal scattering properties to determine the degree of signal contamination, and then to suppress the signal if it is deemed to be contaminated.
Therefore, there exists a need to more accurately identify weather information and to remove ground clutter contamination from a weather radar signal or identify ground in a weather radar signal.
U.S. Pat. No. 6,707,415, which is hereby incorporated by reference, describes a method of using radar to estimate weather and ground reflectivity for the purpose of displaying weather reflectivity relatively uncontaminated by ground signal return, or ground reflectivity that is minimally contaminated by weather. The method makes use of a parameter that represents the relative uncertainty in the current estimates of weather reflectivity and ground normalized radar cross section for all modeled locations. These parameters may or may not be updated in response to new measurements (which reduce the uncertainty in the estimated values). However, in either case starting values for the uncertainty parameters for weather and ground reflectivity must be chosen.
As for any estimation process, the separate estimation of weather and ground reflectivity is not perfect. Occasionally, some weather signal will result in increased estimated ground reflectivity, and vice versa.